import torch
GAME_NAME = "BipedalWalker-v3" # "MountainCarContinuous-v0" "BipedalWalker-v3" "Pendulum-v1"
GAME_UPPER_STEP = 200 # 对不同的环境先估计一条轨迹所用步数的大致上界，仅用于估算经验回放最大长度；对于可无限进行的环境，设置一个最大步数
REWARD_SCALE = 0.1 # 奖励缩放，根据环境奖励大小调整
LEARNING_RATE = 1e-3
DISCOUNT_FACTOR = 0.98

NUM_EPISODES = 2000 # 总共采样轨迹数目

HIDDEN_DIM = 256 # 策略网络PolicyNet隐藏层维度
DEVICE = torch.device("cuda" if torch.cuda.is_available() else "cpu")